With the development and advancement in radio frequency technology, wireless sensor networks (WSNs) have been extended from land to underwater. In the water, WSNs are commonly known as underwater acoustic sensor networks (UASNs). Acoustic signal is used for data transmission in UASNs. However, there are many differences in the transmission between WSNs and UASNs, such as long propagation delay, limited bandwidth, and low data rate, etc. Among which, the most impact in UASNs is long propagation delay.

The design of media access control (MAC) protocol is a topic in wireless networks. Although MAC protocols in terrestrial wireless networks have become broadly studied, the existing protocols cannot be directly applied to UASNs due to the long propagation delay. Long propagation delay causes the collisions in transmission. Therefore, there are many protocols designed to avoid collisions caused by long propagation delay for UASNs. Although these protocols can avoid collisions by deferring a period of time, but their performances in channel utilization are low.

Therefore, this dissertation focuses on two popular technologies in UASNs, termed time division multiple access (TDMA) and four-way handshaking mechanism, and designs the following MAC protocols to suit to UASNs.

(1) In DSS-TDMA (Dynamic Slot Scheduling TDMA-based MAC protocol), the concurrent transmission is taken into consideration. The proposed protocol can not only adapt the schedule dynamically but also use concurrent transmissions to improve the channel utilization.

(2) In CS-MAC (Channel Stealing MAC protocol), a four-way handshaking mechanism with a deferring time period is used to solve the hidden terminal problem. However, the deferring time period causes the low channel utilization. Therefore, in CS-MAC, a strategy is proposed to utilize the waste channel resource and mitigate the exposed terminal problem.

(3) In TLPC (Two-Level Power Control MAC protocol), a four-way handshaking MAC protocol with power control is proposed to avoid collision problems. In TLPC, two collision problems are studied, termed Control/DATA Collision (CDC) and Large Interference Range Collision (LIRC). By power control, TLPC can not only avoid CDC and LIRC problems but also improve the channel utilization.

Simulation results show that the proposed protocols can not only avoid collisions but also improve the channel utilization.

List of Figures
Figure 2.1 The frame structure in DSS-TDMA. 8
Figure 2.2 The network architecture in DSS-TDMA composes of vast underwater sensors and several sinks. Sensors cooperate with each other for detecting or monitoring task. The sensing data also can be either directly or multi-hop forwarded to the sink. 9
Figure 2.3 Slot Constraints. x is a UT slot, y is a UB slot, and z is a UR slot. 11
Figure 2.4 Two kinds of transmission pairs are in the network: (a) The transmission pair without UB slots; (b) The transmission pair with UB slots. 12
Figure 2.5 s1s3 has been transmitting in slot21, and then the states of all the slots are shown in (a). However, slot32
in (b) is a UB slot between s1s3 and s3s1. Therefore, s1s3 and s3s1 should be classified into a group to schedule. 13
Figure 2.6 The benefit of grouping. The UT and UR slots can be reused easily. 14
Figure 2.7 An example scheduling and shifting policy. 16
Figure 2.8 (a) The scheduling results of Group-I; (b) The scheduling results of Group-II. 17
Figure 2.9 The scheduling results of Group-I and Group-II merge into a frame. 17
Figure 2.10 The combination of scheduling results of Group-I and Group-II when traffic loads are high. 18
Figure 2.11 Channel utilization of various protocols for different number of nodes. 22
Figure 2.12 Network throughput generated by various protocols for different offered load in 8 nodes. 23
Figure 2.13 Average packet delay caused by various protocols for different number of nodes. 24
Figure 2.14 One cycle time caused by various protocols for different number of nodes. 25
Figure 3.1 The concept of PCAP mechanism [20]. 28
Figure 3.2 Comparisons of channel utilization among different data rate in terms of data packet size. 33
Figure 3.3 The concept of CS-MAC. 35
Figure 3.4 An example of the idle waiting time division. The time division (a)from back to front; (b)from front to back. 36
Figure 3.5 Three regions are divided in the network. 38
Figure 3.6 The interference at the receiver does not be taken into consideration. 39
Figure 3.7 The interference at the receiver is taken into consideration. 40
Figure 3.8 Comparisons of the network throughput of four protocols in terms of offered load varied from 0.01 to 0.4 packets/s. 43
Figure 3.9 Comparisons of the channel utilization of four protocols in terms of number of nodes varied from 5 to 20 stations. 44
Figure 3.10 Comparisons of the average delay of four protocols in terms of offered load varied from 0.01 to 0.4 packets/s. 45
Figure 4.1 Scenarios of the CDC problem. 49
Figure 4.2 The effectiveness of the CDC problem. 50
Figure 4.3 The effectiveness of the CDC problem in terms of DSR. 51
Figure 4.4 An illustration of the LIRC problem. 52
Figure 4.5 The attenuation and absorption of acoustic wave in terms of DSR. 55
Figure 4.6 An illustration of the interference range in terms of DSR. 58
Figure 4.7 An illustration of TLPC protocol in time domain. 62
Figure 4.8 An illustration of TLPC protocol in space domain. 63
Figure 4.9 The grid topology. 65
Figure 4.10 The comparison of TLPC, APCAP, and Slotted FAMA in terms of number of collisions per STA. (Offered load=0.8) 66
Figure 4.11 The comparison of number of collisions of TLPC, APCAP, Slotted FAMA, and IEEE 802.11 DCF in terms of different traffic loads. 67
Figure 4.12 The comparison of network throughput of TLPC, APCAP, Slotted FAMA, and IEEE 802.11 DCF in terms of different traffic loads. 68
Figure 4.13 The comparison of energy consumption of TLPC, APCAP, Slotted FAMA, and IEEE 802.11 DCF in terms of different traffic loads. 69
Figure 4.14 The comparison of energy consumption per bit of TLPC, APCAP, Slotted FAMA, and IEEE 802.11 DCF in terms of different traffic loads. 70
Figure 4.15 The comparison of network throughput of TLPC, APCAP, Slotted FAMA, and IEEE 802.11 DCF in terms of different traffic loads. 71
Figure 4.16 The comparison of number of collisions of TLPC, APCAP, Slotted FAMA, and IEEE 802.11 DCF in terms of different traffic loads. 72
Figure 4.17 The comparison of energy consumption of TLPC, APCAP, Slotted FAMA, and IEEE 802.11 DCF in terms of different traffic loads. 73
Figure 4.18 The comparison of energy consumption per bit of TLPC, APCAP, Slotted FAMA, and IEEE 802.11 DCF in terms of different traffic loads. 74